Reference

ACT-R is considered a symbolic system in cognitive modeling because it uses symbolic representations and rule-based processes to simulate human cognition. Here’s a brief explanation:

1. Symbolic Representations: ACT-R employs symbolic representations to model knowledge and cognitive processes. It uses structures like production rules and declarative memories to capture how people think and learn.

2. Rule-Based System: The architecture utilizes a production system, which is essentially a collection of formal rules that represent knowledge. These rules define actions or outcomes based on certain conditions, similar to how humans apply learned information to new problems.

3. Integration of Symbolic and Subsymbolic Levels: Although ACT-R primarily uses symbolic processing, it integrates subsymbolic processes to manage learning and decision-making, which helps in simulating human cognitive performance more accurately.

4. Link to Neurocognitive Research: The design of ACT-R aligns with brain functions, as its components map onto different brain regions. This connection enhances its validity as a cognitive model (source).

Images that further illustrate the architecture:

For more detailed reading, refer to this resource.